Many people suffer from Type I or Type II diabetes, in which the body does not properly regulate the blood glucose level. A continuous glucose monitor (CGM) allows the interstitial glucose level of a patient with diabetes to be measured on an ongoing basis, such as every few minutes. The timing and dosage of insulin to administer to the patient may be determined on the basis of measurements recorded by the CGM device. Glucose readings from CGM devices are displayed to the patient, and the patient can inject insulin or consume meals to help control the glucose level. Insulin pumps can deliver precise insulin dosages on a programmable schedule which may be adjusted by the patient or health care provider.
Hazard metrics may be derived from glucose data for assessing a hazard to the diabetic person based on a detected glucose level. For example, a known hazard metric includes the hazard function proposed in the following paper: Kovatchev, B. P. et al., Symmetrization of the blood glucose measurement scale and its applications, Diabetes Care, 1997, 20, 1655-1658. The Kovatchev hazard function is defined by the equation h(g)=[1.509 (log(g)1.0804−5.381)]2, wherein g is the blood glucose concentration (in milligrams per deciliter or mg/dl) and h(g) is the corresponding penalty value. The Kovatchev function provides a static penalty (i.e., hazard) value in that the penalty depends only on the glucose level. The minimum (zero) hazard occurs at 112.5 mg/dl. The hazard with the glucose level approaching hypoglycemia rises significantly faster than the hazard with the glucose level approaching hyperglycemia.
The Kovatchev hazard function fails to account for the rate of change of the glucose level as well as the uncertainty associated with the measured glucose level. For example, a patient's hazard associated with 100 mg/dl and a rapidly falling blood glucose level is likely greater than the patient's hazard associated with 100 mg/dl with a constant glucose rate of change. Further, measured glucose results may be inaccurate due to sensor noise, sensor malfunction, or detachment of the sensor.
Various approaches have been made to control the glucose levels of diabetic people based on CGM glucose data. One approach for limiting the occurrence of hypoglycemic conditions includes an insulin pump shutoff algorithm that completely shuts off the basal insulin if the CGM glucose level drops below a low glucose threshold, such as 50 to 70 mg/dl, and later resumes the basal insulin after a few hours. However, this on/off approach adversely requires the adverse condition of crossing the low glucose threshold to occur before action is taken. Further, this approach does not take into account the speed with which the glucose is crossing the threshold, which may be problematic for patients (e.g., children, active individuals, etc.) with a high rate of glucose change.
Another approach is to alert the patient of predicted hypoglycemia, and the patient then consumes an amount of carbohydrates and waits a predetermined time period. If the system still predicts hypoglycemia the patient repeats the cycle until the system no longer predicts hypoglycemia. However, this approach makes the assumption that the patient is able to consume carbohydrates immediately upon being alerted of the predicted hypoglycemia. Further, the patient may overcorrect by consuming too many carbs, possibly leading to weight gain or to trending the glucose levels towards hyperglycemia.
Accordingly, some embodiments of the present disclosure provide a predictive approach for adjusting a therapy basal rate by mapping the risk of the estimated glucose state to an adjustment of the basal rate based on cumulative hazard values of return paths generated from a glucose state distribution around the estimated glucose state. Risk associated with the glucose state is based on the blood glucose level, the rate of change of the blood glucose level, and the standard deviations of the blood glucose level and rate of change. Further, some embodiments provide for adjusting the calculated risk for a glucose state in response to a meal bolus, an insulin bolus, and/or other events such as exercise, glucagon availability, and stress that may affect the risk of hypoglycemia or hyperglycemia.